Mortality after surgery in Europe: a 7 day cohort study

Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
The Lancet (Impact Factor: 45.22). 09/2012; 380(9847):1059-1065. DOI: 10.1016/S0140-6736(12)61148-9

ABSTRACT The Lancet, 380 (2012) 1059-1065. doi:10.1016/S0140-6736(12)61148-9

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Available from: Rupert M Pearse, Sep 29, 2015
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    • "The trials were chosen because each featured a comparatively large number of local participants and a thorough screening process. The target of trial A was to compare standards of peri-operative care and outcome in 28 European countries [14]. Trial B validated the ability of different biomarkers to predict colorectal cancer stage, survival and response to chemo- and radiotherapy. "
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    ABSTRACT: The necessity to translate eligibility criteria from free text into decision rules that are compatible with data from the electronic health record (EHR) constitutes the main challenge when developing and deploying clinical trial recruitment support systems. Recruitment decisions based on case-based reasoning, i.e. using past cases rather than explicit rules, could dispense with the need for translating eligibility criteria and could also be implemented largely independently from the terminology of the EHR's database. We evaluated the feasibility of predictive modeling to assess the eligibility of patients for clinical trials and report on a prototype's performance for different system configurations. The prototype worked by using existing basic patient data of manually assessed eligible and ineligible patients to induce prediction models. Performance was measured retrospectively for three clinical trials by plotting receiver operating characteristic curves and comparing the area under the curve (ROC-AUC) for different prediction algorithms, different sizes of the learning set and different numbers and aggregation levels of the patient attributes. Random forests were generally among the best performing models with a maximum ROC-AUC of 0.81 (CI: 0.72-0.88) for trial A, 0.96 (CI: 0.95-0.97) for trial B and 0.99 (CI: 0.98-0.99) for trial C. The full potential of this algorithm was reached after learning from approximately 200 manually screened patients (eligible and ineligible). Neither block- nor category-level aggregation of diagnosis and procedure codes influenced the algorithms' performance substantially. Our results indicate that predictive modeling is a feasible approach to support patient recruitment into clinical trials. Its major advantages over the commonly applied rule-based systems are its independency from the concrete representation of eligibility criteria and EHR data and its potential for automation.
    BMC Medical Informatics and Decision Making 12/2013; 13(1):134. DOI:10.1186/1472-6947-13-134 · 1.83 Impact Factor
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    • "Despite tremendous technological and societal improvements over the past several decades, healthcare, especially in the perioperative setting, remains among the most risky activities for a human being [1]. A comparison of ideal, ultra safe, regulated, and dangerous human systems in rates of error per operation lists the categories shown in Table 1 [2]. "
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    ABSTRACT: Patient safety is an issue of imminent concern in the high-risk field of medicine, and systematic changes that alter the way medical professionals approach patient care are needed. Simulation-based training (SBT) is an exemplary solution for addressing the dynamic medical environment of today. Grounded in methodologies developed by the aviation industry, SBT exceeds traditional didactic and apprenticeship models in terms of speed of learning, amount of information retained, and capability for deliberate practice. SBT remains an option in many medical schools and continuing medical education curriculums (CMEs), though its use in training has been shown to improve clinical practice. Future simulation-based anesthesiology training research needs to develop methods for measuring both the degree to which training translates into increased practitioner competency and the effect of training on safety improvements for patients.
    The Scientific World Journal 11/2013; 2013:652956. DOI:10.1155/2013/652956 · 1.73 Impact Factor
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    • "Despite high standards in surgical and anesthetic care in Europe, the perioperative mortality rate is still higher than expected [1]. The aim of goal-directed hemodynamic therapy (GDT), based on the titration of fluids and inotropic drugs to physiological flow-related end points, is to reduce perioperative complications which might even help to reduce perioperative morbidity and mortality [2]. "
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    ABSTRACT: Several single-center studies and meta-analyses have shown that perioperative goal-directed therapy may significantly improve outcomes in general surgical patients. We hypothesized that using a treatment algorithm based on pulse pressure variation, cardiac index trending by radial artery pulse contour analysis, and mean arterial pressure in a study group (SG), would result in reduced complications, reduced length of hospital stay and quicker return of bowel movement postoperatively in abdominal surgical patients, when compared to a control group (CG). 160 patients undergoing elective major abdominal surgery were randomized to the SG (79 patients) or to the CG (81 patients). In the SG hemodynamic therapy was guided by pulse pressure variation, cardiac index trending and mean arterial pressure. In the CG hemodynamic therapy was performed at the discretion of the treating anesthesiologist. Outcome data were recorded up to 28 days postoperatively. The total number of complications was significantly lower in the SG (72 vs. 52 complications, p = 0.038). In particular, infection complications were significantly reduced (SG: 13 vs. CG: 26 complications, p = 0.023). There were no significant differences between the two groups for return of bowel movement (SG: 3 vs. CG: 2 days postoperatively, p = 0.316), duration of post anesthesia care unit stay (SG: 180 vs. CG: 180 minutes, p = 0.516) or length of hospital stay (SG: 11 vs. CG: 10 days, p = 0.929). This multi-center study demonstrates that hemodynamic goal-directed therapy using pulse pressure variation, cardiac index trending and mean arterial pressure as the key parameters leads to a decrease in postoperative complications in patients undergoing major abdominal surgery.Trial registration: NCT01401283.
    Critical care (London, England) 09/2013; 17(5):R191. DOI:10.1186/cc12885 · 4.48 Impact Factor
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